1. Field of the Disclosure
The present disclosure relates generally to an apparatus and method for detecting a signal in a communication system supporting a time division duplexing-code division multiple access (TDD-CDMA) scheme, and more particularly, the present disclosure relates to an apparatus and method for decreasing processing complexity in a communication system supporting a TDD-CDMA scheme.
2. Description of the Related Art
Communication systems have evolved to support a high data rate in order to satisfy a demand for wireless data traffic, which continuously increases. For example, a communication system has evolved to enhance spectral efficiency and increase channel capacity based on various schemes, such as an orthogonal frequency division multiplexing (OFDM) scheme, a multiple-input multiple-output (MIMO) scheme, and the like, in order to increase a data rate.
Cell edge mobile stations (MSs) which are located at a cell edge region, which is far from a cell center in which a signal-to-noise ratio (SNR) is low or a carrier-to-interference and noise ratio (CINR) is low due to the significant impact of an interference from a base station (BS), which is located at a neighbor cell, may decrease system performance of the communication system.
In communication systems, various schemes such as an inter-cell interference-coordination (ICIC) scheme, a coordinated multi-points (CoMP) scheme, an interference cancellation scheme, and the like have been developed in order to increase transmission efficiency for the MSs that are located at the cell edge.
For example, in a communication system supporting a CDMA scheme, various interference cancellation schemes have been used, and typical schemes include a parallel interference cancellation (PIC) scheme, a serial interference cancellation (SIC) scheme, and a joint detection (JD) scheme. Each of the PIC scheme and the SIC scheme is a non-linear interference cancellation scheme, and the JD scheme is a linear interference cancellation scheme.
Generally, performance of a signal detector is proportional to processing complexity and processing computation amount. The greater a requirement for the performance of the signal detector is, the greater is the complexity for implementing the signal detector. Thus, it is very important in a communication system for the signal detector to be implemented with low complexity.
Recently, with respect to communication systems supporting a CDMA scheme and a communication system supporting time division-synchronous code division multiple access (TD-SCDMA), a signal detector has been implemented using a joint detector which is implemented by using a JD scheme. The joint detector models a receiving system as one linear matrix system based on a multi-code received signal and a channel estimation result, and detects an optimal received symbol by detecting a linear minimum mean square error (LMMSE) solution in the modeled linear matrix system.
A signal detection scheme which is based on the JD scheme in a communication system supporting the TD-SCDMA scheme will be described below.
For modeling the JD scheme, the following will be assumed.
A signal received in a radio frequency (RF) integrated circuit (IC) is output to an analog to digital converter (ADC) converter, and the ADC samples the signal received in the RF IC to generate a digital signal. The ADC over-samples the signal received in the RF IC N times, e.g., twice, and it will be assumed that the signal sampled in the ADC has a rate of chip×2.
In the communication system supporting the TD-SCDMA scheme, it will be assumed that signal receiving apparatuses, e.g., MSs, use a plurality of receiving antennas, e.g., two receiving antennas.
It will be assumed that the communication system supporting the TD-SCDMA scheme may support K channelization codes. Further, it will be assumed that the kth channelization code from among the K channelization codes is c(k), and channel impulse responses (CIRs) for two antenna paths which are estimated from a channel estimator included in a signal receiving apparatus are h0 and h1. If the signal receiving apparatus uses two antennas such as an antenna #0 and an antenna #1, a CIR for an antenna path for the antenna #0 is h0, and a CIR for an antenna path for the antenna #1 is h1.
The kth channelization code c(k) may be expressed using Equation (1):c(k)=[c0(k),c1(k), . . . ,c2Q−1(k)]  (1)
In Equation (1), Q denotes a spreading factor, and c2Q−1(k) denotes a channelization code element included in the kth channelization code c(k). That is, the kth channelization code c(k) includes 2Q channelization code elements.
The CIR h0 may be expressed using Equation (2):h0=[h0,0,h0,1 . . . ,h0,2W−1]  (2)
In Equation (2), W denotes a tap length of a related CIR, and h0,2QW−1 denotes a CIR element included in the CIR h0. That is, the CIR h0 includes 2W CIR elements.
The CIR h1 may be expressed using Equation (3):h1=[h1,0,h1,1 . . . ,h1,2W−1]  (3)
In Equation (3), h1,2W−1 denotes a CIR element included in the CIR h1. That is, the CIR h1 includes 2W CIR elements.
It will be assumed that a data symbol which a signal transmitting apparatus, e.g., a BS, transmits is d, and a received signal vector in which a Gaussian noise is extracted is x. One data block includes at least one data symbol. It will be assumed that the number of modulation symbols which are transmitted based on each channelization code in one data block, e.g., quadrature amplitude modulation (QAM) symbols, is N. In this case, the number of QAM symbols included in one data block is K*N.
The data symbol d may be expressed using Equation (4):d=[d0(0),d0(1), . . . ,d0(K−1),d1(0), . . . ,dN−1(K−1)]T  (4)
In Equation (4), denotes a data symbol element included in a data symbol. That is, one data symbol includes K*N data symbol elements. So, a data symbol element becomes a QAM symbol in Equation (4). In Equation (4), T denotes a transpose.
The received signal vector x may be expressed using Equation (5):x=[x0,0,x1,0 . . . ,x1,M(2NQ+2W−1)]T  (5)
In Equation (5), x1,M(2NQ+2W−1) denotes a received signal vector element included in the received signal vector x. That is, the received signal vector x includes 2*M(2NQ+2W) received signal vector elements.
A received signal modeling in a case that one channelization code is used in a conventional communication system supporting a TD-SCDMA scheme will be described with reference to FIG. 1.
FIG. 1 is a diagram illustrating a received signal modeling in a case where one channelization code is used in a conventional communication system supporting a TD-SCDMA scheme.
Referring to FIG. 1, in a signal transmitting apparatus, a data symbol element d0(k) is multiplied by a channelization code c(k), and the multiplied signal is transmitted. A CIR h0 is reflected on the signal transmitted in the signal transmitting apparatus, so a signal receiving apparatus receives a received signal vector element such as d0(k)(h0*c(k)).
A transmitted signal modeling in a case where a plurality of channelization codes are used in a conventional communication system supporting a TD-SCDMA scheme will be described with reference to FIG. 2.
FIG. 2 is a diagram illustrating a transmitted signal modeling in a case where a plurality of channelization codes are used in a conventional communication system supporting a TD-SCDMA scheme.
Referring to FIG. 2, a transmitted signal modeling in a case where a plurality of channelization codes, e.g., three channelization codes, are used and the number of QAM symbols, which are transmitted based on each of the three channelization codes is N, is illustrated. It is noted that only 3*3 QAM symbols from among 3*N QAM symbols are illustrated in FIG. 2.
A structure of a matrix V in a conventional communication system supporting a TD-SCDMA scheme will be described with reference to FIG. 3.
FIG. 3 is a diagram illustrating a structure of a matrix V in a conventional communication system supporting a TD-SCDMA scheme.
Referring to FIG. 3, a system equation for a signal detector in the communication system supporting the TD-SCDMA scheme may be defined based on a received signal modeling as described in FIG. 1 and a transmitted signal modeling as described in FIG. 2.
In FIG. 1, a transmitted signal, i.e., a data symbol d, is spread based on a channelization code c, and a convolution computation with a CIR h is performed on a spread data symbol d*c which is generated by spreading the data symbol d based on the channelization code c. A system through which the data symbol d passes is given as a convolution form between the channelization code c and the CIR h, i.e., a vector b. It will be assumed that a vector b for the kth channelization code c(k) is b(k).
So, b(k) for a CIR h0 may be expressed using Equation (6):b0(k)=h0*c(k)=[b0,0(k),b0,1(k), . . . ,b0,1Q+2W−1(k)]  (6)
In Equation (6), 0 denotes the b(k) for the CIR h0.
Further, b(k) for a CIR h1 may be expressed using Equation (7):b1(k)=h1*c(k)=[b1,0(k),b1,1(k), . . . ,b1,2Q+2W−1(k)]  (7)
In Equation (7), b1(k) denotes the b(k) for the CIR h1.
If the vector b(k) is regarded as one column, vectors b for K channelization codes, i.e., K vectors b, may be included in one matrix, and it will be assumed that the one matrix is a matrix V. In the matrix V, a vector b for an arbitrary channelization code c is generated as one column, so the matrix V includes K columns.
The matrix V is defined for one of N QAM symbols. In order to generate a system matrix for all locations of the N QAM symbols, i.e., all QAM symbols included in one data block, N matrices V for the N QAM are be concatenated by cascading the N matrices V.
It will be assumed that the system matrix which is generated by the matrices V for the N QAM symbols is a matrix T. That is, the matrix T is a matrix including the matrices V which are generated for the N QAM symbols.
In this case, a system equation in which a Gaussian noise is considered may be expressed using Equation (8):Td+n=y  (8)
In Equation (8), n denotes the Gaussian noise, and y denotes a received signal vector which includes the Gaussian noise n.
A solution for the system equation in which the Gaussian noise is considered as expressed in Equation (8) may be expressed using Equation (9):{circumflex over (d)}=(THT+σ2I)−1THy  (9)
In Equation (9), {circumflex over (d)} denotes an estimated data symbol, a denotes a covariance of the Gaussian noise n, H denotes Hermitian, and I denotes an identity matrix. That is, the solution for the system equation in which the Gaussian noise is considered is an estimated data symbol {circumflex over (d)}.
A structure of a matrix T in a conventional communication system supporting a TD-SCDMA scheme will be described with reference to FIG. 4.
FIG. 4 is a diagram illustrating a structure of a matrix T in a conventional communication system supporting a TD-SCDMA scheme.
Referring to FIG. 4, a size of the matrix T is very large, so an operation of detecting a pseudo-inverse matrix of (THT+σ2I) requires a complex processing computation amount, as expressed as Equation (8).
If 16 channelization codes are used and one data block includes 22 QAM symbols in the communication system, the number of columns included in the matrix T is 352 (i.e., 16×22). If it is considered that processing computation amount of an inverse matrix is proportional to a cube of a matrix size, a processing computation amount necessary for processing one data block is greater than or equal to tens of mega flops.
It is impossible to process this processing computation amount using conventional hardware or a digital signal processing (DSP) core. This processing computation amount, however, significantly increases power consumption of a signal receiving apparatus.
Accordingly, there is a need for a scheme of detecting a signal for decreasing processing complexity, processing computation amount, and power consumption.